Droplet: A New Denial-of-Service Attack on Low Power Wireless Sensor Networks

In this paper we present a new kind of Denial-of-Service attack against the PHY layer of low power wireless sensor networks. Overcoming the very limited range of jamming-based attacks, this attack can penetrate deep into a target network with high power efficiency. We term this the Droplet attack, as it attains enormous disruption by dropping small, payload-less frame headers to its victim's radio receiver, depriving the latter of bandwidth and sleep time. We demonstrate the Droplet attack's high damage rate to full duty-cycle receivers, and further show that a high frequency version of Droplet can even force nodes running on very low duty-cycle MAC protocols to drop most of their packets

Resilient networking in wireless sensor networks

This report deals with security in wireless sensor networks (WSNs), especially in network layer. Multiple secure routing protocols have been proposed in the literature. However, they often use the cryptography to secure routing functionalities. The cryptography alone is not enough to defend against multiple attacks due to the node compromise. Therefore, we need more algorithmic solutions. In this report, we focus on the behavior of routing protocols to determine which properties make them more resilient to attacks. Our aim is to find some answers to the following questions. Are there any existing protocols, not designed initially for security, but which already contain some inherently resilient properties against attacks under which some portion of the network nodes is compromised? If yes, which specific behaviors are making these protocols more resilient? We propose in this report an overview of security strategies for WSNs in general, including existing attacks and defensive measures. In this report we focus at the network layer in particular, and an analysis of the behavior of four particular routing protocols is provided to determine their inherent resiliency to insider attacks. The protocols considered are: Dynamic Source Routing (DSR), Gradient-Based Routing (GBR), Greedy Forwarding (GF) and Random Walk Routing (RWR)

A Mixed-Integer Programming Approach for Jammer Placement Problems for Flow-Jamming Attacks on Wireless Communication Networks

In this dissertation, we study an important problem of security in wireless networks. We study different attacks and defense strategies in general and more specifically jamming attacks. We begin the dissertation by providing a tutorial introducing the operations research community to the various types of attacks and defense strategies in wireless networks. In this tutorial, we give examples of mathematical programming models to model jamming attacks and defense against jamming attacks in wireless networks. Later we provide a comprehensive taxonomic classification of the various types of jamming attacks and defense against jamming attacks. The classification scheme will provide a one stop location for future researchers on various jamming attack and defense strategies studied in literature. This classification scheme also highlights the areas of research in jamming attack and defense against jamming attacks which have received less attention and could be a good area of focus for future research. In the next chapter, we provide a bi-level mathematical programming model to study jamming attack and defense strategy. We solve this using a game-theoretic approach and also study the impact of power level, location of jamming device, and the number of transmission channels available to transmit data on the attack and defense against jamming attacks. We show that by increasing the number of jamming devices the throughput of the network drops by at least 7%. Finally we study a special type of jamming attack, flow-jamming attack. We provide a mathematical programming model to solve the location of jamming devices to increase the impact of flow-jamming attacks on wireless networks. We provide a Benders decomposition algorithm along with some acceleration techniques to solve large problem instances in reasonable amount of time. We draw some insights about the impact of power, location and size of the network on the impact of flow-jamming attacks in wireless networks

A Mixed-Integer Programming Approach for Jammer Placement Problems for Flow-Jamming Attacks on Wireless Communication Networks

In this dissertation, we study an important problem of security in wireless networks. We study different attacks and defense strategies in general and more specifically jamming attacks. We begin the dissertation by providing a tutorial introducing the operations research community to the various types of attacks and defense strategies in wireless networks. In this tutorial, we give examples of mathematical programming models to model jamming attacks and defense against jamming attacks in wireless networks. Later we provide a comprehensive taxonomic classification of the various types of jamming attacks and defense against jamming attacks. The classification scheme will provide a one stop location for future researchers on various jamming attack and defense strategies studied in literature. This classification scheme also highlights the areas of research in jamming attack and defense against jamming attacks which have received less attention and could be a good area of focus for future research. In the next chapter, we provide a bi-level mathematical programming model to study jamming attack and defense strategy. We solve this using a game-theoretic approach and also study the impact of power level, location of jamming device, and the number of transmission channels available to transmit data on the attack and defense against jamming attacks. We show that by increasing the number of jamming devices the throughput of the network drops by at least 7%. Finally we study a special type of jamming attack, flow-jamming attack. We provide a mathematical programming model to solve the location of jamming devices to increase the impact of flow-jamming attacks on wireless networks. We provide a Benders decomposition algorithm along with some acceleration techniques to solve large problem instances in reasonable amount of time. We draw some insights about the impact of power, location and size of the network on the impact of flow-jamming attacks in wireless networks

Exploring Impacts of Random Proactive Jamming Attack in Wireless Sensor Network

Wireless Sensor networks are one of the most extensively used technologies in our day to day lives; they can provide communication without needing a fixed infrastructure, which makes them suitable for communication in disaster areas or when quick deployment is needed. However, this kinds of network technology uses the wireless medium for communication. It is vulnerable to malicious attacks. One of the most frequently used attacks is a random jamming attacks which is Denial of Service attack. Random Jamming attacks disturb the communication between Sink and legitimate nodes. In rough environments where there is constant traffic, Random jamming attack can cause serious problems. Because of this, a study of random jamming attacks and how to prevent them is necessary. In this research the random jamming attacks were simulated using Riverbed Modeler software, in order to provide a better understanding of effects of random jamming attacks. This study will be helpful for future research and development of a practical, effective way to avoid random jamming attacks. The objectives of this thesis were to simulate and analysis wireless sensor network (ZigBee) under random jamming attacks; launch different kinds of (fixed, mobile) random jamming attacks in order to test how much influence on performance of wireless sensor network. Riverbed Modeler Based simulation which have five scenarios were created and the simulation was run and the results were collected, which shows that the throughput of the wireless sensor network decrease and increase the delay ,data drop when the network is affected by the random Jammers. Finally, thesis describe the open issues in this field, such as adding more than one random jammer and sink in wireless sensor network